Title: 🚻 1.7. Gender equality in the digital era
Course: "Our networks, our security" Digital Security with a Gender Perspective > Section: Our internet, Our Rights: Basic Concepts

As I continued researching, I also discovered that the Internet’s dimensions are not limited to just technical aspects.

Beyond the Computer

The internet is not just a technical asset; it is also a powerful tool for political, social, cultural, and economic change. It enables people to participate in the economy, access healthcare services, connect with others who share similar interests, and engage in formal and informal decision-making processes concerning social, cultural, and political life.

On an individual level, the internet is a critical resource that allows people to build and express their individuality, gender, and sexuality. It is a powerful enabler of human rights, development, and social justice.

For women and girls, the internet has become a vital tool in the fight against gender inequality, providing new spaces for freedom and empowerment. It has allowed us to expand our narratives, engage in public spheres, and assert our human rights by accessing education and culture.

However, the Internet does not exist independently of the material, economic, political, and ideological conditions from which it emerged – conditions that have historically placed women in positions of subordination and disadvantage, as compared to men. This reality is reflected in the gender digital gap, which refers to the disparity between men and women accessing and using digital technologies. Globally, 70% of men use the internet compared to 65% of women, resulting in 244 million more men online than women in 2023. In some countries, this gap is even wider, limiting women’s opportunities for education, employment, and social participation.

While access to the Internet has increased over the past two decades creating new opportunities for women, the systemic gender inequality seen in the offline world has also extended into cyberspace, where women and girls continue to be victims of discrimination and gender-based violence.

On the following sites, you will find more information about the links between gender equality and the Internet:

GenderIT.org:https://www.genderit.org/

GenderIT - Feminist Principles of the Internet:https://www.genderit.org/articles/feminist-principles-internet

United Nation Women: Placing gender equality at the heart of the Global Digital Compact: Taking forward the recommendations of the sixty seventh session of the Commission on the Status of Women

Building a Feminist Internet – https://www.apc.org/en/project/feminist-internet

AI and Gender Equality. Why It Matters?

As we mentioned before, AI is transforming our world, from how we search for information to how decisions are made in hiring, healthcare, and even law enforcement. While AI offers many benefits, it also carries risks—especially when it comes to gender equality. AI systems are only as good as the data they learn from, and if that data reflects historical biases, AI can end up reinforcing and even amplifying discrimination. This means AI has the power to either challenge or deepen gender inequalities.

When we talk about gender equality in the digital age, we have to consider AI. Who creates it? How is it designed? And who benefits from it? These questions matter because AI affects everyone—but not always equally. If we don’t take gender into account, AI could end up reinforcing existing biases rather than creating a fairer, more inclusive world.

The Gender Gap in AI Development

The tech industry has long struggled with gender diversity, and AI is no exception. Women represent only 29% of the AI workforce 👉(FORBES, 2024), indicating a significant gender gap in this field. This underrepresentation leads to a lack of diverse perspectives, increasing the risk of biased algorithms. Consequently, AI solutions may overlook or inadequately address issues that disproportionately impact women.

Gender Bias in AI

AI is designed to learn from data, but what happens when that data carries biases from the real world? Unfortunately, AI doesn’t just reflect reality—it can amplify inequalities, making existing gender biases even worse. Since AI systems analyze patterns and make predictions based on past information, they can unknowingly perpetuate discrimination. Let’s break down how this happens and why it matters.

- How do AI Systems Inherit Gender Bias?

Imagine an AI-powered hiring tool trained on past job applications. If most leadership positions in the dataset were historically filled by men, the AI might assume that men are better candidates for these roles—even if women are equally qualified. Similarly, AI language models, like those used in chatbots, can pick up on societal stereotypes. For instance, if the data used to train them associates “nurse” with women and “engineer” with men, the AI may reinforce these biases in responses and translations.

Facial recognition software is another area where bias appears. Studies have shown that these systems often perform worse on women and people with darker skin tones because the training datasets are predominantly made up of white male faces. This can lead to errors in identification, with serious consequences in security and policing.

Even in healthcare, AI bias can put lives at risk. Medical AI systems, which assist in diagnosing diseases or recommending treatments, are frequently trained on male-centric data. This means they may not recognize symptoms that present differently in women, leading to misdiagnosis or inadequate treatment recommendations.

- Bias in Algorithm Design

Bias doesn’t just come from data—it can also stem from the way AI is built. If the teams developing AI systems lack diversity, there’s a higher chance that biases will go unnoticed. Consider virtual assistants like Siri or Alexa. Many of these AI-powered assistants default to female voices and are programmed to be helpful, reinforcing outdated stereotypes of women as subservient caregivers.

Another example is automated translation software. Some languages, like English, use gender-neutral words, but AI systems often inject gender biases into translations. A sentence like “The doctor is smart” might be translated into another language as “He is smart,” while “The nurse is caring” might become “She is caring.” These subtle reinforcements of gender roles may seem minor, but they shape perceptions over time.

AI-facilitated gender-based violence

AI can be both a tool for combating and perpetuating gender-based violence. On the negative side, AI tools can be misused to create deepfakes, which are increasingly used to harass and blackmail women, causing real-world harm. Social media algorithms, driven by AI, may also unintentionally amplify harmful gender stereotypes and allow harassment to spread more easily. At the same time, AI is being used for good—such as in detecting and removing abusive content, tracking online harassment patterns, and supporting survivors through AI-driven reporting tools.

In the next module, we will explore these risks and solutions in greater detail, examining real-world examples of how AI is shaping the fight against gender-based violence.